Dust/sand electrification, which is a ubiquitous phenomenon in dust events, has a potentially dramatic effect on dust/sand lifting and transport processes. However, the effect of such electrification is still largely unclear, mainly due to its complexity and sparse observations. Here, we conducted an extensive observational analysis involving mild and severe dust storms with minimum visibility, ranging from ~ 0.09 to 0.93 km, to assess the electrical properties of airborne dust particles in dust storms. The space charge density has been estimated indirectly based on Gauss’s law. Using the wavelet coherence analysis that is a method for evaluating the correlations between two non-stationary time series in the time-frequency domain, we found that the space charge density and dust concentration were significantly correlated over the 10 min timescales that is on the order of the typical integral time scale of atmospheric turbulence. We further presented a simple linear regression (SLR) model to quantify such large timescale correlations and found that there was a significant linear relationship between space charge density and dust concentration at given ambient temperature and relative humidity (RH), suggesting that the estimated mean charge-to-mass ratio of dust particles was expected to remain constant (termed as the equilibrium value μ *). In addition, the influences of ambient temperature and RH on μ * were evaluated by a multiple linear regression (MLR) model, showing that the μ * is nonlinearly related to environmental factors. The present study provides observational evidence for the environmental-dependent electrification equilibrium effects in dust storms. This finding may reduce challenges in future quantifications of dust electrification, as it is possible to exclude effects, such as the particles’ collisional dynamics, on dust electrification.